Matthias Feurer

Thanks @skubatur for picking this up. I don't have a strong preference. I'm wondering what a good name for `X` would be, though. I wouldn't call it features as this...

Hi, I deciding this on a case-by-case basis makes sense. Answers about the existing cases: * How do we know that these should be bools and not categoricals? Since the...

> Yes, but we already converted the stringy "True" and "False" to boolean True and False. You mean in Python? If that's the case, we should continue doing this I...

Hey @AndriyMulyar is this still an issue for you? We do by now have task creation in Python, so I guess we can close this?

That is a great suggestion. I think providing a standard `to_latex` would be great, so the tables in different papers look similar, which would reduce cognitive overhead. Could we also...

It turns out that this is a well-known issue in scikit-learn: https://github.com/scikit-learn/scikit-learn/issues/17675

I fully agree to this suggestion. Indeed, dataframes were added later and have matured substantially since then and I guess we can consider handling them standard knowledge for machine learners.

Sounds good to me. In addition to NEP29 we should always strive to support the python version of the latest Ubuntu LTS and Google Colab as a lot of people...

No, this means that there are categorical features that cannot be handled by the current pipeline. Is this an example we use in the documentations? If yes, we need to...

Alright, can you confirm that the other snippet works for you? Thanks a lot for the link, so [this page](https://github.com/openml/docs/blob/master/docs/benchmark.md) needs to be updated. Would you like to create a...